CRAN
mRMRe 2.0.9
"Parallelized Minimum Redundancy, Maximum Relevance (mRMR) Ensemble Feature Selection"
Released Feb 14, 2019 by Benjamin Haibe-Kains
This package can be loaded by Renjin but 16 out 23 tests failed.
Dependencies
"Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique with DOI: N De Jay et al. (2013)
Installation
Maven
This package can be included as a dependency from a Java or Scala project by including
the following your project's pom.xml file.
Read more
about embedding Renjin in JVM-based projects.
<dependencies>
<dependency>
<groupId>org.renjin.cran</groupId>
<artifactId>mRMRe</artifactId>
<version>2.0.9-b1</version>
</dependency>
</dependencies>
<repositories>
<repository>
<id>bedatadriven</id>
<name>bedatadriven public repo</name>
<url>https://nexus.bedatadriven.com/content/groups/public/</url>
</repository>
</repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:mRMRe')
Test Results
This package was last tested against Renjin 0.9.2724 on Feb 16, 2019.
- adjacencyMatrix-examples
- causality-examples
- cgps-examples
- correlate-examples
- featureCount-examples
- featureData-examples
- featureNames-examples
- get.thread.count-examples
- mRMRe.Data-class-examples
- mRMRe.Filter-class-examples
- mRMRe.Network-class-examples
- mim-examples
- priors-examples
- sampleCount-examples
- sampleNames-examples
- sampleStrata-examples
- sampleWeights-examples
- scores-examples
- set.thread.count-examples
- solutions-examples
- subsetData-examples
- target-examples
- visualize-examples